Dynamic Service Reconfiguration with Multi-agent Systems

Most modern manufacturing systems rely on constantly seeking new solutions to better fulfil their manufacturing objectives. As reported in today’s manufacturing literature, dynamic service reconfiguration is one solution that permits to endorse continuous service reconfiguration, flexibility and evolvable systems. In spite of the current research efforts, real reconfiguration solutions are still lacking automated tools that support dynamic and runtime reconfigurations by discovering new adaptation needs and opportunities and, thus, explore possible actions leading to new system configurations. To overcome these issues, it is essential to provide solutions that answer to the “when” and “what” to reconfigure questions. Most of the service changes triggers rely on reactive events, where decisions come from a centralized decision-maker and are performed manually. Based on these facts a service-oriented multi-agent systems architecture is described aiming at actively promoting service reconfiguration (e.g., improvement of the service’s properties and/or update the services’ catalogue) to cope with the unexpected and unpredictable condition changes. This paper describes the processes that decide which service reconfiguration should be applied to each circumstance. The developed prototype for a flexible manufacturing system case study allowed verifying the feasibility of the proposed dynamic service reconfiguration solution in different scenarios.

[1]  Nelson Rodrigues,et al.  Self-interested Service-Oriented Agents Based on Trust and QoS for Dynamic Reconfiguration , 2015, Service Orientation in Holonic and Multi-agent Manufacturing.

[2]  Jing Zhou,et al.  Integrated reconfiguration and age-based preventive maintenance decision making , 2007 .

[3]  Vicent J. Botti,et al.  ANEMONA-S + Thomas: A Framework for Developing Service-Oriented Intelligent Manufacturing Systems , 2015, Service Orientation in Holonic and Multi-agent Manufacturing.

[4]  Amro M. Farid,et al.  Measures of reconfigurability and its key characteristics in intelligent manufacturing systems , 2014, J. Intell. Manuf..

[5]  Stamatis Karnouskos,et al.  Factory of the Future: A Service-oriented System of Modular, Dynamic Reconfigurable and Collaborative Systems , 2010 .

[6]  Anne L'Anton,et al.  A modeling framework for manufacturing services in Service-oriented Holonic Manufacturing Systems , 2016, Eng. Appl. Artif. Intell..

[7]  Francis G. McCabe,et al.  Reference Model for Service Oriented Architecture 1.0 , 2006 .

[8]  José Barbosa,et al.  Specification of the PERFoRM architecture for the seamless production system reconfiguration , 2016, IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society.

[9]  Paulo Leitão,et al.  Benchmarking flexible job-shop scheduling and control systems , 2013 .

[10]  Pedro Neves,et al.  Reconfiguration Methodology to improve the agility and sustainability of Plug and Produce Systems , 2016 .

[11]  Mauro Onori,et al.  The IDEAS project: plug & produce at shop‐floor level , 2012 .

[12]  Tsung-Hsien Yang,et al.  Intelligent Service Reconfiguration for Home Robots , 2016 .

[13]  Luis Ribeiro,et al.  An agent based framework to support plug and produce , 2014, 2014 12th IEEE International Conference on Industrial Informatics (INDIN).

[14]  Nelson Rodrigues,et al.  Triggering strategies for automatic and online service reconfiguration , 2016, 2016 11th Iberian Conference on Information Systems and Technologies (CISTI).

[15]  Freddy Lécué,et al.  SOA4All: An Innovative Integrated Approach to Services Composition , 2010, 2010 IEEE International Conference on Web Services.

[16]  Raymond A. Paul,et al.  Dynamic System Reconfiguration Via Service Composition for Dependable Computing , 2005, Monterey Workshop.